Monte Carlo simulations can be very time-consuming. You can change a number of factors that affect the speed of simulations. The factors are listed below in order of importance:
In the Speed tab of the Run Preferences dialog are options that can substantially increase the speed of the simulation. Of course, if the Extreme Speed setting is available, you can experience dramatic cuts in run times.
If the model is incompatible with Extreme speed or the license does not include it, you can, in increasing order of helpfulness:
Use the precision control feature.
The precision control feature can be used to either increase the precision of the simulations or increase the speed of the simulations. If you set the confidence level to a high number, the simulations will be more precise, but might run significantly longer. However, if you do not need as precise a result, you can set the confidence level to a lower number and the simulation speed will increase.
Using this feature to speed up the model will require you to experiment with different confidence levels.
Reduce the size of the model by reducing the number of assumptions, forecasts, and correlations.
Large models require more time per trial. For example, a model that takes 3 or 4 seconds per recalculation cycle will take up to an hour to simulate 1,000 trials.
Greater numbers of assumptions and forecasts slow the simulation, especially if the assumptions and forecasts are scattered across many spreadsheets in the model. Start by examining the structure and nature of the model to locate possible efficiencies. You can also use the sensitivity feature or the Tornado Chart tool to determine which assumptions contribute the least amount of uncertainty to the most important forecasts. Freeze or eliminate the least important assumptions from the simulation.
Correlated assumptions can also consume a significant amount of processing time; the time grows geometrically as the number of correlated assumptions increases.
Reduce the use of other applications.
Quitting other applications and closing or minimizing windows can be helpful in reducing overhead and increasing simulation speed.
The amount of RAM in the computer has a large effect on the speed of simulations. Modern operating systems give applications such as spreadsheets the appearance of additional RAM through the use of virtual memory.
Virtual memory enables you to run a greater number of applications than would otherwise be possible, but slows down overall processing speed because the system is frequently accessing the hard drive. If you hear the hard disk being used during a simulation, there might not be enough RAM to hold all parts of the simulation. Buying more RAM or turning off virtual memory (if possible) are solutions to this problem.